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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 8/2017

27.07.2017 | Original Paper

Survey on zoom-lens calibration methods and techniques

verfasst von: Shirazi Muhammad Ayaz, Min Young Kim, Jaechan Park

Erschienen in: Machine Vision and Applications | Ausgabe 8/2017

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Abstract

This paper surveys zoom-lens calibration approaches, such as pattern-based calibration, self-calibration, and hybrid (or semiautomatic) calibration. We describe the characteristics and applications of various calibration methods employed in zoom-lens calibration and offer a novel classification model for zoom-lens calibration approaches in both single and stereo cameras. We elaborate on these calibration techniques to discuss their common characteristics and attributes. Finally, we present a comparative analysis of zoom-lens calibration approaches, highlighting the advantages and disadvantages of each approach. Furthermore, we compare the linear and nonlinear camera models proposed for zoom-lens calibration and enlist the different techniques used to model the camera’s parameters for zoom (or focus) settings.
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Metadaten
Titel
Survey on zoom-lens calibration methods and techniques
verfasst von
Shirazi Muhammad Ayaz
Min Young Kim
Jaechan Park
Publikationsdatum
27.07.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 8/2017
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-017-0863-1

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